PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Rheumatol. Author manuscript; available in PMC 2010 October 7.
Published in final edited form as:
PMCID: PMC2951477
NIHMSID: NIHMS234013

Spondyloarthritis Is Associated with Poor Function and Physical Health-Related Quality of Life

Abstract

Objective

To study physical function and health-related quality of life (HRQOL) in US veterans with spondyloarthritis (SpA).

Methods

In a postal survey of 70,334 eligible veterans, demographics, performance of activities of daily living (ADL), and HRQOL, by Veterans Short Form-36, were queried; 58% responded (n = 40,508). Databases provided International Classification of Diseases, 9th ed. codes for ankylosing spondylitis (AS), psoriatic (PsA) and reactive arthritis (ReA), comorbidities, and demographics. Multivariable linear/logistic regressions compared ADL limitations and HRQOL in SpA versus non-SpA, and predictors in SpA.

Results

Six hundred sixty-four veteran respondents had diagnoses of SpA: AS, n = 100; PsA, n = 551; ReA, n = 13. Veterans with AS, PsA, and ReA had significantly more limitations in dressing (44%, 23%, 24% vs 22%; p = 0.0002), transferring (57%, 42%, 64% vs 39%; p = 0.0006), walking (74%, 57%, 67% vs 54%; p = 0.0005), and overall mean ADL limitations (2.5, 1.7, 2.1 vs 1.6; p < 0.0001) compared to veterans without SpA, after multivariable adjustment. Limitations in each ADL in patients with SpA were 1.3–5.3 times that of an age-matched US cohort. Physical HRQOL was significantly lower compared with non-SpA veterans (p < 0.0001 for physical component summary, physical functioning, role physical, and bodily pain; p = 0.004 for general health) and age-sex-matched US norms; all differences exceeded clinically meaningful threshold of 5–10 units. More limitations in ADL were significantly associated with lower physical component summary scores in patients with AS and with lower physical and mental component summary scores in PsA.

Conclusion

After adjustment for differences in demographics and comorbidities, poorer physical function and HRQOL were observed in patients with SpA. Strategies focused to improve/maintain functional status are important for treatment of SpA.

Key Indexing Terms: PSORIATIC ARTHRITIS, ANKYLOSING SPONDYLITIS, REACTIVE ARTHRITIS, FUNCTIONAL LIMITATION, HEALTH-RELATED QUALITY OF LIFE

Spondyloarthritis (SpA) includes a group of common diseases such as ankylosing spondylitis (AS), psoriatic arthritis (PsA), and reactive arthritis (ReA). SpA is prevalent, affecting 1%–3% in the general population13. Many elegant studies have reported that functional status213 and health-related quality of life (HRQOL)8,1420 are impaired in these patients. Functional status is a strong driver of total and direct costs2123. Functional limitations, as assessed by performance of activities of daily living (ADL)3,5,7,10 or using validated instruments2,4,6,8,9,1113, are commonly reported by patients with SpA. Most previous studies had no comparison group26,10,11,13, except a few that compared subgroups of patients with each other (AS vs PsA) or to patients with rheumatoid arthritis (RA)79,12. Similar rates of functional limitations in SpA versus RA and AS versus PsA8,9,12 were reported. The published literature has several limitations: (1) most included patients referred to specialty clinics and none were population-based and therefore may have limited generalizability; (2) analyses were not adjusted for confounders such as age, sex, or comorbidities, all of which affect physical function2426; and (3) with the exception of 3 series4,9,12, most had small sample sizes < 200. Thus, we need population-based studies of functional status in patients with SpA to improve our understanding of the independent effect of SpA on patients’ functional status. Such studies should control for important confounders such as comorbidity and sociodemographics.

Ware has proposed that the best means to understand burden of disease in a specific population is to compare it with the general population27. Generic measures, such as the Medical Outcomes Study Short Form-36 (SF-36), allow comparisons across disease-specific populations and provide information on disease consequences that disease-specific HRQOL measures may fail to detect28. Three studies that compared HRQOL of patients with AS15,16 and PsA14 to the general population reported significantly lower HRQOL on physical and to a lesser extent on psychosocial domains — raw scores15 or age-sex-adjusted scores14,16 were lower. There is a renewed interest in HRQOL and functional status of patients with SpA due to availability of new effective biologic therapies. However, with the exception of a Norwegian population-based study15, these data have been reported in clinical trial16 or tertiary referral center populations14 that are not representative of community-based SpA patient populations.

The objective of our study was to determine impairments in physical function and HRQOL in a population-based cohort of patients with SpA receiving care at Veterans Affairs (VA) medical facilities. The VA represents the largest integrated healthcare system in the US, providing healthcare to more than 4.9 million subjects, and with a budget of $25 billion in 200329. It is well-suited for a population based study of SpA, as it has one of the most advanced computerized medical record systems, arthritis is the fifth most common medical condition in veterans30, and the VA provides care to a male-predominant population. Thus, in this population-based cohort, we aimed to (1) compare reported performance of ADL and HRQOL in veterans with AS, PsA, and ReA to those without SpA and to matched US cohorts; and (2) study if HRQOL in patients with SpA are attributable to sociodemographics, functional limitations, and/or comorbidities.

MATERIALS AND METHODS

Patient population

Details of the original study, the Veterans Quality of Life (Vet-QoL) study, have been published31. The study was approved by the Minneapolis VA Institutional Review Board. VISN-13 is a network of in- and outpatient medical facilities providing medical care to veterans in the geographical area consisting of North Dakota, South Dakota, Minnesota, and selected counties of Iowa, Nebraska, Wisconsin, and Kansas. Veterans with out- or inpatient encounters at a VA facility in this network during an 18-month period (October 31, 1996 to March 31, 1998) and a valid mailing address received a survey. Nonresponders received a reminder survey; survey response rate was 58% (40,508/70,334). Survey data were supplemented by administrative information, including International Classification of Diseases, 9th ed. (ICD-9) diagnoses codes for AS (720.0), PsA (696.0), and ReA (099.3, 711.11–711.19), race, employment status, age, and sex. ICD-9 codes were extracted for all VA encounters for the year prior to the survey from patient treatment and out-patient datasets. Diagnoses of AS, PsA, and ReA in the Minneapolis VA databases were found to have high specificity and predictive values of 89%–100% and good sensitivity of 71%–100%32.

Survey data

The survey included questions regarding age, race, sex, marital status, education level, functional and health status. Physical function was assessed querying limitations (no, some, unable) in 6 ADL (bathing, dressing, eating, transferring to and from chair, walking, and using the toilet) — the Katz ADL index, a validated measure of ADL ability33, used very commonly in cohort studies34,35. HRQOL was measured using Short Form-36 for Veterans (SF-36V), a valid and reliable questionnaire assessing 8 domains including physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role emotional (RE), and mental health (MH)36. Physical component (PCS) and mental component summary (MCS) scores are calculated from the 8 domains, norm-based and standardized with a mean of 50 and a standard deviation (SD) of 10. SF-36 has been widely used in health surveys in the general population as well as in rheumatologic diseases37,38, and shown to be valid and reliable in patients with PsA14,18 and AS15,16,3941.

Outcomes of interest

Impairment in physical function was assessed by patient-reported limitations in ADL; HRQOL by SF-36V domain and summary scores. Each ADL limitation was categorized as any versus no limitation (dichotomous), and total ADL limitations ranging 0–6, categorized into “no”: 0 ADL, “moderate”: 1–2 ADL, or “severe limitations”: ≥ 3 ADL, similar to previous studies34,42. “Clinically meaningful” differences were based on definitions for minimal clinically important differences (MCID) of 5–10 points in domain and 2.5–5 points in summary component scores of SF-36 derived from published randomized controlled trials in AS, RA, osteoarthritis, PsA, and systemic lupus erythematosus16,4346. SF-36 PCS and MCS scores were divided into quartiles for regression analyses.

Predictors of interest and confounders/covariates

The predefined hypothesis of the study was that patients with AS, PsA, or ReA would have poorer functional status and HRQOL than the general population without SpA, in unadjusted and multivariable-adjusted analyses. Based on reports in other medical conditions4749, multivariate analyses for functional limitations and HRQOL were adjusted for potential confounders, including (1) demographics: age (yrs), sex (male/female), race (white vs other), education level (< grade 8, grade 8–11, high school graduate, or college and beyond), employment status (employed, unemployed, retired, unknown), marital status (married, not married); (2) comorbidity: sum of comorbidities including asthma/chronic obstructive pulmonary disease (COPD), depression, diabetes, hypertension, or heart disease (comorbidity scale ranging from 0–5); and (3) current smoking status (smoker vs nonsmoker). To study predictors of physical and mental/emotional HRQOL (using PCS and MCS scores), ADL limitations and comorbidities were considered the main predictors of interest.

Analyses

Chi-square tests and independent sample t-tests were used for categorical and continuous variables, respectively, comparing SpA to non-SpA patients. ADL limitations were compared to an age-matched US cohort from the San Luis Valley Health and Aging Study that used stratified sampling on age and ethnicity of residents age ≥ 60 years from 2 rural Southern Colorado counties35. SF-36V domain scores of patients with AS or PsA (too few patients with ReA) were compared to age- and sex-matched US population norms — since 98%–99% of AS/PsA patients were men, age-matched US means for men were utilized50.

We compared unadjusted and multivariable-adjusted least-means square scores for the SF-36V subscales, PCS and MCS scores between patients with AS, PsA, and ReA compared to those without SpA using linear regression. The proportion with each ADL limitation and overall proportion with no, moderate, or severe ADL limitations were similarly compared using logistic regression analyses. Multivariable regression models were adjusted for sociodemographic, comorbidity, and smoking status, as described above. Since conclusions based on adjusted estimates were not different from those based on unadjusted estimates, i.e., estimates were robust regardless of adjustments for sociodemographics, comorbidity, and smoking status, both estimates are presented in the main tables, but only multivariable adjusted estimates are discussed.

In patients with AS and PsA, logistic regression analyses assessed predictors for reporting the worst quartile of SF-36V PCS or MCS scores. In addition to sociodemographics, comorbidity, and current smoking status described above, multivariable analyses modeled ADL limitations described above as covariates for these regression analyses. Regression analyses were not performed individually in patients with ReA due to small numbers. All analyses were performed using SPSS version 11.0.1 (SPSS Inc., Chicago, IL, USA). A p value < 0.05 was considered significant.

RESULTS

Demographic and clinical characteristics of patients with AS, PsA, and ReA

Of the 70,991 veterans, 70,334 were eligible, i.e., were alive and had a valid mailing address. Overall, 1,001/70,991 patients had diagnoses of SpA: AS (n = 154), PsA (n = 814), and ReA (n = 33). Of the 40,508 survey respondents (58%), 100 had AS, 551 had PsA, and 13 had ReA. Table 1 presents sociodemographic characteristics in veterans with and without SpA. Patients with SpA were predominantly men, with a mean age ranging from 46 to 65 years. Compared to the general veteran population, patients with PsA had more comorbidities, and those with ReA were younger, more likely to be female, employed, or current smokers, with fewer comorbidities.

Table 1
Demographic and clinical characteristics of patients with ankylosing spondylitis, psoriatic arthritis, and reactive arthritis and subjects without spondyloarthritis.

Survey nonresponders were significantly less likely to be married (47% vs 64.9%) or retired (26.7% vs 43.9%) and were younger (56.3 vs 64.5 yrs), as compared with responders.

More functional limitations in SpA than non-SpA patients

After multivariable adjustment, patients with AS, PsA, and ReA reported greater mean ADL limitations than patients without SpA (2.5, 1.7, and 2.1 vs 1.6; p < 0.0001; Table 2); significantly more limitations in dressing (43.8%, 22.6%, and 23.7% vs 22.1%; p = 0.0002), transferring (57.4%, 42.3%, and 64.1% vs 38.8%; p = 0.0006), and walking (74%, 56.6%, and 67.2% vs 53.7%; p = 0.0005), respectively. Smaller but significant differences were evident for difficulty in bathing (41.2%, 26.8%, and 29.5% vs 25.7%; p = 0.026) and eating (25.6%, 11.8%, and 21.7% vs 14%; p = 0.026). No differences were noted in limitations using toilet.

Table 2
Unadjusted and multivariable adjusted least-means squared scores (with 95% confidence intervals) for health related quality of life (HRQOL) and functional limitation in patients with and without spondyloarthritis (SpA).

Comparison to an age-matched US cohort aged 60 years or older from San Luis Valley, the frequency of limitation of bathing, dressing, transferring, eating, and toileting was 1.3–3 times in our patients with SpA ≥ 60 years (Figure 1). The limitation in walking was 3.7–5.3 times as frequent. Overall ADL limitation of any ADL 1–2 or ≥ 3 ADL was 1.3–2.3 times as compared to this age-matched US cohort (Figure 1).

Figure 1
Activities of daily living (ADL) limitations in patients with ankylosing spondylitis (AS), psoriatic arthritis (PsA), and reactive arthritis (ReA) age 60 years and older compared to a US cohort from San Luis Valley, CO, of similar age. Patients with AS, ...

Poorer HRQOL in patients with SpA

As presented in Table 2, patients with AS, PsA, and ReA reported significantly lower/poorer multivariable adjusted scores in physical functioning, role physical, bodily pain, general health domains, and PCS, compared to veterans without SpA. Reported differences were most marked between patients with AS and non-SpA and approached clinically meaningful levels in physical HRQOL domains, and were less in those with ReA or PsA. No differences were noted in social functioning, role emotional, vitality, mental health, and MCS domains.

Compared to age- and sex-matched US norms, AS and PsA patients reported significant deficits in physical domains (34%–50% reductions) and less but still significant deficits in general health/vitality (27%–36% lower) and mental/emotional domains (11%–29% reductions) (Figure 2).

Figure 2
Short Form-36 for Veterans (SF-36V) subscale scores in patients with ankylosing spondylitis (AS) and psoriatic arthritis (PsA) compared to age- and sex-matched US general population. SV-36V scores were lower on all domains in patients with AS and PsA ...

Predictors of HRQOL in patients with AS and PsA

Tables 3 and and44 show predictors significantly associated with poorer HRQOL in patients with AS and PsA, respectively. In general, a significant proportion of variability was explained by the regression models (R2 ranging from 0.21 to 0.65). In patients with AS, severe limitations in ADL were significantly associated with lower PCS score, and being retired with better MCS scores (Table 3). In patients with PsA, more ADL limitations were significantly associated with lower PCS and MCS scores, and unemployed status with lower PCS scores (Table 4).

Table 3
Significant predictors of HRQOL in patients with ankylosing spondylitis in multivariable adjusted analyses*. Only significant predictors are listed in the table.
Table 4
Significant predictors of HRQOL in patients with psoriatic arthritis in multivariable adjusted analyses. Only significant predictors are listed in the table.

DISCUSSION

Our study demonstrated significantly more ADL limitations and poorer HRQOL in a population-based sample of patients with AS, PsA, and ReA compared to those without SpA and to age-sex-matched US norms. Certain ADL were more limited in patients with SpA than others, i.e., patients with AS, PsA, and ReA reported more limitations in walking, dressing, and transferring than non-SpA patients. Since we used a generic measure of function, i.e., Katz ADL index, we could compare the ADL limitation rates to age-matched US cohorts, which revealed significantly more ADL limitations in our SpA cohorts. That patients with AS, PsA, and ReA report statistically significantly and clinically meaningful lower physical HRQOL domain scores compared with non-SpA patients, but similar psychosocial HRQOL, indicates that the major morbidity related to these conditions is physical. These observations confirm earlier similar findings of lower reported physical HRQOL in patients with AS15,16,19,40,41 and PsA14,18, and extend these to the veteran population. To our knowledge, this is the first study describing HRQOL and functional status of US veterans with SpA.

Our study has several limitations. The results may not be generalizable to community-dwelling non-veterans with SpA, or to other VA networks, due to geographical differences and nonresponse bias. However, there are fewer generalizability issues compared to previous studies that included patient cohorts from tertiary centers, subject to selection/referral bias due to selection of patients with more severe disease2,3,8,12,15,18 or clinical trials that usually exclude patients with significant comorbidity. A much higher prevalence of PsA than AS in this cohort may be due to many possible reasons. This includes higher comorbidity in veterans compared to the age-matched general US population51, the survey being sent only to veterans seeking health-care (rather than all inhabitants in a geographic area) who are likely to have higher comorbidity, and overcoding of psoriasis patients with joint pain as PsA (and perhaps under-coding of AS). Cross-sectional survey studies have found prevalence of PsA as high as 0.4% in the general population52. Although SpA cohorts were identified using ICD-9 codes, we have already demonstrated that the ICD-9 codes have high sensitivity, specificity, and predictive values in our VA databases32. We had no data on non-VA diagnoses of SpA. These misclassification biases (including overcoding of PsA) would bias our findings towards null, and therefore would make our estimates conservative. We do not have any information on the severity of comorbidities or SpA or spinal versus peripheral involvement, which would have allowed us to examine the association of disease severity and type of presentation with HRQOL.

The strengths of our study include (1) a large population-based sample; (2) use of generic measures of HRQOL and functional status that allowed comparisons to other matched US cohorts; (3) the robustness of estimates with small changes with multivariable adjustment; (4) adjustment for important confounders including sociodemographics and comorbidity characteristics; and (5) good model-fit for predictors of HRQOL in patients with AS and PsA that explained a large proportion of variability.

Reductions in PCS are 1 SD lower and in MCS similar to those reported previously in an AS cohort that was 15 years younger with 70% men40. This may be due to an older cohort (mean age 58–63 yrs vs 24–51 yrs in earlier studies), sex differences (98% vs 63%–93% men), and more comorbidities in veterans compared with the US general population51. This signifies that veterans with SpA may have even poorer HRQOL than community-dwelling patients with SpA, confirming a similar finding reported for all veterans versus age-matched US controls53, a finding likely secondary to higher comorbidity reported in veterans51.

Our findings of far lower physical HRQOL (34%–50% lower) and lower psychosocial HRQOL (11%–29% lower) in veterans with SpA compared to the age-sex-matched US population are much larger than reported in a clinical trial16, likely due to lower comorbidity in clinical trial populations and higher comorbidity in our veteran cohorts. Mean PCS scores of 28.9 in AS, 34.1 in PsA, and 36.8 in ReA patients are very low compared with age-sex-matched US norms. Approximately 6%, 10%, and 13% of the US general population report PCS scores at or below these levels, respectively50. On the other hand, MCS scores of 47.9 in AS, 45.6 in PsA, and 40.6 in ReA reflected less decrements in HRQOL; 33%, 28%, and 19% of the general population report MCS scores at or below these levels, respectively50.

These findings suggest that the major emphasis of comprehensive care of patients with SpA should be aimed at improving physical HRQOL. This may be achieved by prevention, early diagnosis, and treatment of SpA-associated physical morbidity and of associated medical comorbidity, both of which are likely to improve HRQOL and function. These results should prompt more population-based studies of HRQOL in patients with SpA to further understand relationships of predictors of health outcomes. The earlier studies from tertiary care rheumatology practices are skewed towards the more symptomatic patients and therefore are unlikely to give an assessment of burden at the community level, as noted in a comprehensive review54.

With very few previous studies of HRQOL and functional status in patients with ReA20, our study provides data that both HRQOL and functional status are diminished in patients with ReA, similar to other SpA. Our study is limited by the small number of patients with ReA. Further studies are needed to better understand these deficits in patients with ReA.

Our finding of the association of more limitations in ADL with poorer HRQOL in AS confirms similar observations in 2 small cohorts of juvenile AS55 and AS56. This adds ADL limitations to the list of significant predictors of HRQOL in AS in multivariable analyses described previously, including current employment, disease activity, coping strategy, fatigue40, education level40,41, and female sex41. Our findings that more ADL limitations predict poorer physical and mental HRQOL, and unemployed status mental HRQOL, in PsA are novel, and need to be confirmed in future studies. In conjunction with recent findings that function in patients with SpA is a strong correlate of total and direct costs2123 and of healthcare utilization57, this implies that strategies aimed at improving function in patients with SpA (physical and occupational therapy, decreasing disease activity, and optimal control of comorbidity) may improve HRQOL and decrease costs. Our multivariable adjusted models explained a significant proportion of variability, 40%–65%, in PCS and MCS scores in AS and PCS scores in PsA, and had good model-fit characteristics.

This population-based study of US veterans with AS, PsA, and ReA demonstrated functional limitations were higher and physical HRQOL was lower in patients with SpA compared to patients without SpA, even after adjustment for age, sociodemographics, and comorbidities. Functional limitations and HRQOL deficits were far greater than age-matched and age-sex-matched US norms, respectively. We need studies that assess which of the following factors contribute to these differences, including: severity and duration of disease, response to current therapy, treatment-related adverse effects, medical comorbidity, socioeconomic factors, and healthcare access. Many of these factors are modifiable, and targeted interventions can potentially improve function and HRQOL in patients with SpA.

Acknowledgments

Supported by National Institutes of Health CTSA Award 1 KL2 RR024151-01 (Mayo Clinic Center for Clinical and Translational Research).

References

1. Salaffi F, De Angelis R, Stancati A, Grassi W. Health-related quality of life in multiple musculoskeletal conditions: A cross-sectional population based epidemiological study. II. The mapping study. Clin Exp Rheumatol. 2005;23:829–39. [PubMed]
2. Bostan EE, Borman P, Bodur H, Barca N. Functional disability and quality of life in patients with ankylosing spondylitis. Rheumatol Int. 2003;23:121–6. [PubMed]
3. Dagfinrud H, Kjeken I, Mowinckel P, Hagen KB, Kvien TK. Impact of functional impairment in ankylosing spondylitis: Impairment, activity limitation, and participation restrictions. J Rheumatol. 2005;32:516–23. [PubMed]
4. Doran MF, Brophy S, MacKay K, Taylor G, Calin A. Predictors of longterm outcome in ankylosing spondylitis. J Rheumatol. 2003;30:316–20. [PubMed]
5. Gran JT, Skomsvoll JF. The outcome of ankylosing spondylitis: A study of 100 patients. Br J Rheumatol. 1997;36:766–71. [PubMed]
6. Guillemin F, Briancon S, Pourel J, Gaucher A. Long-term disability and prolonged sick leaves as outcome measurements in ankylosing spondylitis. Possible predictive factors. Arthritis Rheum. 1990;33:1001–6. [PubMed]
7. Hidding A, van Santen M, De Klerk E, et al. Comparison between self-report measures and clinical observations of functional disability in ankylosing spondylitis, rheumatoid arthritis and fibromyalgia. J Rheumatol. 1994;21:818–23. [PubMed]
8. Sokoll KB, Helliwell PS. Comparison of disability and quality of life in rheumatoid and psoriatic arthritis. J Rheumatol. 2001;28:1842–6. [PubMed]
9. Zink A, Braun J, Listing J, Wollenhaupt J. Disability and handicap in rheumatoid arthritis and ankylosing spondylitis — results from the German rheumatological database. German Collaborative Arthritis Centers. J Rheumatol. 2000;27:613–22. [PubMed]
10. Wordsworth BP, Mowat AG. A review of 100 patients with ankylosing spondylitis with particular reference to socioeconomic effects. Br J Rheumatol. 1986;25:175–80. [PubMed]
11. van Tubergen A, Landewe R, Heuft-Dorenbosch L, et al. Assessment of disability with the World Health Organisation Disability Assessment Schedule II in patients with ankylosing spondylitis. Ann Rheum Dis. 2003;62:140–5. [PMC free article] [PubMed]
12. Zink A, Thiele K, Huscher D, et al. Healthcare and burden of disease in psoriatic arthritis. A comparison with rheumatoid arthritis and ankylosing spondylitis. J Rheumatol. 2006;33:86–90. [PubMed]
13. Heikkila S, Viitanen JV, Kautiainen H, Kauppi M. Functional long-term changes in patients with spondylarthropathy. Clin Rheumatol. 2002;21:119–22. [PubMed]
14. Husted JA, Gladman DD, Farewell VT, Long JA, Cook RJ. Validating the SF-36 health survey questionnaire in patients with psoriatic arthritis. J Rheumatol. 1997;24:511–7. [PubMed]
15. Dagfinrud H, Mengshoel AM, Hagen KB, Loge JH, Kvien TK. Health status of patients with ankylosing spondylitis: A comparison with the general population. Ann Rheum Dis. 2004;63:1605–10. [PMC free article] [PubMed]
16. Davis JC, van der Heijde D, Dougados M, Woolley JM. Reductions in health-related quality of life in patients with ankylosing spondylitis and improvements with etanercept therapy. Arthritis Rheum. 2005;53:494–501. [PubMed]
17. Hidding A, de Witte L, van der Linden S. Determinants of self-reported health status in ankylosing spondylitis. J Rheumatol. 1994;21:275–8. [PubMed]
18. Husted JA, Gladman DD, Farewell VT, Cook RJ. Health-related quality of life of patients with psoriatic arthritis: A comparison with patients with rheumatoid arthritis. Arthritis Rheum. 2001;45:151–8. [PubMed]
19. Ozgul A, Peker F, Taskaynatan MA, Tan AK, Dincer K, Kalyon TA. Effect of ankylosing spondylitis on health-related quality of life and different aspects of social life in young patients. Clin Rheumatol. 2006;25:168–74. [PubMed]
20. Soderlin MK, Kautiainen H, Skogh T, Leirisalo-Repo M. Quality of life and economic burden of illness in very early arthritis. A population based study in southern Sweden. J Rheumatol. 2004;31:1717–22. [PubMed]
21. Ara RM, Packham JC, Haywood KL. The direct healthcare costs associated with ankylosing spondylitis patients attending a UK secondary care rheumatology unit. Rheumatology. 2008;47:68–71. [PubMed]
22. Kobelt G, Sobocki P, Mulero J, Gratacos J, Pocovi A, Collantes-Estevez E. The burden of ankylosing spondylitis in Spain. Value Health. 2008;11:408–15. [PubMed]
23. Zhu TY, Tam LS, Lee VW, et al. Costs and quality of life of patients with ankylosing spondylitis in Hong Kong. Rheumatology. 2008;47:1422–5. [PubMed]
24. Tuttolomondo A, Pedone C, Pinto A, et al. Predictors of outcome in acute ischemic cerebrovascular syndromes: The GIFA Study. Int J Cardiol. 2008;125:391–6. [PubMed]
25. Friedman JI, Harvey PD, McGurk SR, et al. Correlates of change in functional status of institutionalized geriatric schizophrenic patients: Focus on medical comorbidity. Am J Psychiatry. 2002;159:1388–94. [PubMed]
26. Wan GJ, Counte MA, Cella DF, Hernandez L, Deasy S, Shiomoto G. An analysis of the impact of demographic, clinical, and social factors on health-related quality of life. Value Health. 1999;2:308–18. [PubMed]
27. Ware JE., Jr Using generic measures of functional health and well-being to increase understanding of disease burden. Spine. 2000;25:1467. [PubMed]
28. Guyatt GH, Feeny DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med. 1993;118:622–9. [PubMed]
29. Perlin JB, Kolodner RM, Roswell RH. The Veterans Health Administration: Quality, value, accountability, and information as transforming strategies for patient-centered care. Am J Manag Care. 2004;10:828–36. [PubMed]
30. Yu W, Ravelo A, Wagner T, et al. Prevalence and costs of chronic conditions in the VA health care system. Med Care. 2003;60:146S–67S. [PubMed]
31. Singh JA, Borowsky SJ, Nugent S, et al. Health-related quality of life, functional impairment, and healthcare utilization by veterans: Veterans’ Quality of Life Study. J Am Geriatr Soc. 2005;53:108–13. [PubMed]
32. Singh JA, Holmgren AR, Krug H, Noorbaloochi S. Accuracy of the diagnoses of spondylarthritides in Veterans Affairs medical center databases. Arthritis Rheum. 2007;57:648–55. [PubMed]
33. Katz SFA, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in aged: The index of ADL: A standard measure of biological and psychological function. JAMA. 1963;185:914–9. [PubMed]
34. Dunlop DD, Semanik P, Song J, Manheim LM, Shih V, Chang RW. Risk factors for functional decline in older adults with arthritis. Arthritis Rheum. 2005;52:1274–82. [PMC free article] [PubMed]
35. Hamman RF, Mulgrew CL, Baxter J, Shetterly SM, Swenson C, Morgenstern NE. Methods and prevalence of ADL limitations in Hispanic and non-Hispanic white subjects in rural Colorado: The San Luis Valley Health and Aging Study. Ann Epidemiol. 1999;9:225–35. [PubMed]
36. Selim AJ, Berlowitz D, Fincke G, et al. Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration. Int J Qual Health Care. 2006;18:43–50. [PubMed]
37. Ware JE, Jr, Sherbourne CD. The MOS 36-item Short-form Health Survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30:473–83. [PubMed]
38. Ware JE, Jr, Snow KK, Kosinski M. SF-36 health survey: Manual and interpretation guide. Lincoln, RI: Quality Metric Inc; 2000.
39. Haywood KL, Garratt AM, Dziedzic K, Dawes PT. Generic measures of health-related quality of life in ankylosing spondylitis: Reliability, validity and responsiveness. Rheumatology. 2002;41:1380–7. [PubMed]
40. Chorus AM, Miedema HS, Boonen A, Van Der Linden S. Quality of life and work in patients with rheumatoid arthritis and ankylosing spondylitis of working age. Ann Rheum Dis. 2003;62:1178–84. [PMC free article] [PubMed]
41. Ward MM. Health-related quality of life in ankylosing spondylitis: A survey of 175 patients. Arthritis Care Res. 1999;12:247–55. [PubMed]
42. Dunlop DD, Manheim LM, Song J, Chang RW. Arthritis prevalence and activity limitations in older adults. Arthritis Rheum. 2001;44:212–21. [PubMed]
43. Strand V. Longer term benefits of treating rheumatoid arthritis: Assessment of radiographic damage and physical function in clinical trials. Clin Exp Rheumatol. 2004;22:S57–64. [PubMed]
44. Strand V, Crawford B. Improvement in health-related quality of life in patients with SLE following sustained reductions in anti-dsDNA antibodies. Exp Rev Pharmacoeconomics Outcomes Res. 2005;5:317–26. [PubMed]
45. Strand V, Kelman A. Outcome measures in osteoarthritis: Randomized controlled trials. Curr Rheumatol Rep. 2004;6:20–30. [PubMed]
46. Tugwell P, Wells G, Strand V, et al. Clinical improvement as reflected in measures of function and health-related quality of life following treatment with leflunomide compared with methotrexate in patients with rheumatoid arthritis: Sensitivity and relative efficiency to detect a treatment effect in a twelve-month, placebo-controlled trial. Leflunomide Rheumatoid Arthritis Investigators Group. Arthritis Rheum. 2000;43:506–14. [PubMed]
47. Heo S, Moser DK, Lennie TA, Zambroski CH, Chung ML. A comparison of health-related quality of life between older adults with heart failure and healthy older adults. Heart Lung. 2007;36:16–24. [PubMed]
48. Chisholm MA, Spivey CA, Nus AV. Influence of economic and demographic factors on quality of life in renal transplant recipients. Clin Transplant. 2007;21:285–93. [PubMed]
49. Borowiak E, Kostka T. Predictors of quality of life in older people living at home and in institutions. Aging Clin Exp Res. 2004;16:212–20. [PubMed]
50. Ware JE, Jr, Kosinski M, Keller SK. SF-36 physical and mental health summary scales: A user’s manual. Boston, MA: The Health Institute; 1994.
51. Agha Z, Lofgren RP, Van Ruiswyk JV, Layde PM. Are patients at Veterans Affairs medical centers sicker? A comparative analysis of health status and medical resource use. Arch Intern Med. 2000;160:3252–7. [PubMed]
52. Salaffi F, De Angelis R, Grassi W. Prevalence of musculoskeletal conditions in an Italian population sample: Results of a regional community-based study. I. The mapping study. Clin Exp Rheumatol. 2005;23:819–28. [PubMed]
53. Kazis LE, Miller DR, Clark J, et al. Health-related quality of life in patients served by the Department of Veterans Affairs: Results from the Veterans Health Study. Arch Intern Med. 1998;158:626–32. [PubMed]
54. Ward MM. Quality of life in patients with ankylosing spondylitis. Rheum Dis Clin North Am. 1998;24:815–27. x. [PubMed]
55. Duarte-Salazar C, Guzman-Vazquez S, Soto-Molina H, et al. Disability impact on quality of life in Mexican adults with juvenile idiopathic arthritis and juvenile ankylosing spondylitis. Clin Exp Rheumatol. 2007;25:922–7. [PubMed]
56. Turan Y, Duruoz MT, Cerrahoglu L. Quality of life in patients with ankylosing spondylitis: A pilot study. Rheumatol Int. 2007;27:895–9. [PubMed]
57. Singh J, Strand V. Health care utilization in patients with spondyloarthropathies. Rheumatology. 2009 Jan 16; [Epub ahead of print] [PMC free article] [PubMed]